Network traffic simulation

About: Network traffic simulation is a research topic. Over the lifetime, 4535 publications have been published within this topic receiving 74606 citations.

Game network traffic simulation by a custom bot

Abstract: Minecraft is a popular video game played worldwide, and is built simply enough to be used for network analysis and research. This paper describes an automated software agent created to simulate player traffic within the game. Realistic network traffic simulation was the goal that inspired the creation of our “Minecraft bot”: an automatic program or bot that could act in similar ways to a real player, and be able to be mass produced to saturate a local area network. This will facilitate network research by allowing users to have a more scalable testing environment and thus enable controlled laboratory experiments that are impossible to set up in live online gaming environments. The basic commands in Minecraft consist of moving, placing and breaking blocks (pieces of environment) and a realistic bot needs to replicate these actions. Another important objective was to have the ability to create hundreds or thousands of bots doing the same actions, to be able to create artificial latency on the network. This paper will go through the entire lifecycle of our project, starting with some information on existing research about the subject, and how it relates to ours. Following that we describe our bot requirements, the work that was done to find a pre-built solution, the solution we ended up using and how it was modified to fit our requirements. We then have a section showing performance experiments we ran, which compared the packet count and traffic volume between players and bots, as well as cpu usage statistics as more connections were made to the server to ensure that our server hardware was not a factor in our network testing. The final section is the conclusion which talks about the outcome of our project in relation to our original goals, and how it will impact future research in this area.

Microscopic online simulations of urban traffic

Abstract: In this paper a concept for online simulations of urban road networks is developed, with real-time traffic data from induction loops serving as input for microscopic simulations From the simulations, estimates of traffic conditions for regions which are not adequately covered by measurements are determined The quality of the reproduced traffic states with regard to vehicle densities and link travel times is investigated The dynamic data are processed by a route guidance system based on a fuzzy logic approach As an example of dynamic traffic management, different strategies for individual en-route guidance systems and their efficiencies are studied The study area is the road network of Duisburg

Model-based throughput prediction in data center networks

Abstract: In this paper, we address the problem of performance analysis in computer networks. We present a new meta-model designed for the performance modeling of network infrastructures in modern data centers. Instances of our metamodel can be automatically transformed into stochastic simulation models for performance prediction. We evaluate the approach in a case study of a road traffic monitoring system. We compare the performance prediction results against the real system and a benchmark. The presented results show that our approach, despite of introducing many modeling abstractions, delivers predictions with errors less than 32% and correctly detects bottlenecks in the modeled network.

Accelerated Simulation of Discrete Event Dynamic Systems via a Multi-Fidelity Modeling Framework

Abstract: Simulation analysis has been performed for simulation experiments of all possible input combinations as a “what-if” analysis, which causes the simulation to be extremely time-consuming. To resolve this problem, this paper proposes a multi-fidelity modeling framework for enhancing simulation speed while minimizing simulation accuracy loss. A target system for this framework is a discrete event dynamic system. The dynamic property of the system facilitates the development of variable fidelity models for the target system due to its high computational cost; and the discrete event property allows for determining when to change the fidelity within a simulation scenario. For formal representation, the paper defines several key concepts such as an interest region, a fidelity change condition, and a selection model. These concepts are integrated into the framework to allow for the achievement of a condition-based disjunction of high- and low-fidelity simulations within a scenario. The proposed framework is applied to two case studies: unmanned underwater and urban transportation vehicles. The results show that simulation speed increases at least 1.21 times with a 5% accuracy loss. We expect that the proposed framework will resolve a computationally expensive problem in the simulation analysis of discrete event dynamic systems.

A new traffic model and statistical admission control algorithm for providing QoS guarantees to on-line traffic

Abstract: On-line traffic, including conversational calls, videoconference calls, and live video, is becoming an important type of traffic in the Internet. The traffic traces of on-line traffic are not pre-recorded, which means little information on the on-line traffic is known in advance. Hence, on-line traffic is hard to characterize by existing traffic models, such as D-BIND. In order to anticipate and capture the burstiness property of on-line traffic, we introduce a new confidence-level-based statistical bounding interval-length dependent (S-BIND) traffic model and a statistical admission control algorithm, based on the S-BIND traffic model: the GammaH-BIND algorithm. Our simulation results show that by using the S-BIND traffic model as inputs, the GammaH-BIND algorithm can achieve the maximum valid network utilization for both low-bursty and high-bursty on-line traffic, which is 50%/spl sim/70% higher than the achievable network utilization under the D-BIND traffic model.